Method for operating a laser cutting installation, laser cutting installation and system

Abstract

The invention relates to a method for operating a laser cutting installation, comprising the following steps: a) providing a data set comprising an image of a machined workpiece with a cutting edge and comprising objective cutting edge features attributed to the image; b) displaying the image of the cutting edge from the data set on a display device, wherein the cutting edge differs in accordance with the objective cutting edge features; c) user inputting an evaluation of the displayed cutting edge; d) creating and / or optimizing user-individual operating parameters of the laser cutting installation in accordance with the user inputting of the evaluation of the cutting edge.

Description

Technical Field

[0001] The present invention relates to a method for operating a laser cutting facility, a laser cutting facility for laser cutting, and a system comprising the laser cutting facility and a display device constructed independently of the laser cutting facility. Background Technology

[0002] Laser cutting equipment is particularly used for cutting workpieces made of metal or other materials. The optimal cutting process must be designed with considerations of cut quality, cutting speed, gas consumption, robustness to disturbances, and machine autonomy. In principle, the cutting process can be optimized for all three criteria, but at least cut quality and cutting speed are mutually exclusive.

[0003] EP 4 119 284 A1 discloses the calibration of a quality evaluator for industrial laser processing, wherein, immediately after laser processing, the quality evaluator uses imaging methods to inspect and measure the cutting edge characteristics of the workpiece's cut edge, thereby obtaining objective cutting edge characteristics such as roughness, burrs, and slag adhesion. The operating parameters of the laser processing are then optimized based on the obtained cutting edge characteristics.

[0004] Operating parameters are optimized by associating the cutting edge characteristics with various operating parameters. Then, based on the cutting edge characteristics obtained by the quality evaluator, the operating parameters are changed to improve, for example, roughness, burrs, and slag adhesion.

[0005] However, this leads to operating parameters being adjusted uniformly for all cutting edge characteristics without considering the individualized requirements of the user (especially the machine operator), shift supervisor, company, or industry. This is problematic because the perception of laser-cut edge quality is subjective. Summary of the Invention

[0006] Therefore, the purpose of this invention is to provide user-individualized and optimized operating parameters for laser cutting facilities.

[0007] The object of the present invention is achieved by a method having the features of claim 1. The method for operating a laser cutting facility includes the following method steps, particularly the following method steps performed in the given order: a) Provide a dataset containing images of processed workpieces with cut edges and including objective cut edge features associated with the images; b) Displaying an image of the cut edge from the dataset on a display device, wherein the cut edge differs / does not vary according to the objectified cut edge features; c) User input to evaluate the displayed cut edges; d) Based on user input evaluating the cut edge, create and / or optimize user-individualized operating parameters for the laser cutting facility.

[0008] Therefore, when creating and / or optimizing operating parameters, the user's individualized and / or subjective quality requirements can be considered. Here, the user is unaware of how the operating parameters are affected because they are only evaluating the cutting edge itself. This further helps to objectify the user's evaluation. Furthermore, the user's evaluation, particularly their input regarding their individualized and / or subjective quality requirements, is facilitated through user input. Therefore, the user does not need to process a large number of complex cutting edge features but can easily and quickly perform the evaluation based on the image. Here, associating the cutting edge features with the image of the cutting edge is preferably done in the background.

[0009] Displaying the cut edge and its objective cut edge features as images rather than numerical values ​​provides a simple graphical visualization of the objective cut edge features, making it quite easy for users to make decisions about the desired cut edge result. Here, the image is used as a representation of the objective cut edge features. At this point, the user is not clear about which objective cut edge feature or degree they prefer, or what operating parameters they derive from it.

[0010] One or more of the following features can be considered as objectifiable and / or objective cutting edge features: roughness, burrs, slag adhesion, discoloration, and uniformity.

[0011] For example, 3D point clouds can be generated for burrs and cut edges. Objective main or sub-measures can be derived from the point cloud, such as the average maximum burr value (Bp value), average roughness value (Ra), and / or average roughness depth (Rz) at different depths.

[0012] Advantageously, the creation and / or optimization of individualized operating parameters are also based on the material being processed. Therefore, individualized quality can be provided for each material.

[0013] Preferably, when displaying an image of the cut edge, the objective measurement of the cut edge features is not displayed, that is, the specific values ​​of the cut edge features are not displayed.

[0014] Advantageously, especially after step d), the following method steps are performed: e) Use the created and / or optimized operating parameters to cut the workpiece, especially to perform laser cutting.

[0015] Therefore, individualized operating parameters can be used to cut the workpiece.

[0016] To provide the dataset, advantageous improvements to the method include the following method steps, which are performed in particular in the listed order: - Process the parts to produce a part with at least one cut edge; - Capture an image of the cut edge; - Measure the cutting edge to objectify the cutting edge features; - Assigning objective cut edge features to the image; and - Store the image and its associated objectified cut edge features in the dataset.

[0017] Therefore, the dataset contains at least one image with a cut edge and one or more cut edge features associated with that image.

[0018] Advantageously, processing the workpiece in step a) for generating the dataset results in as many combinations as possible of the cutting edge features and their degree. The number of images can preferably be determined according to the following formula: , Where x corresponds to the number of cutting edge features considered, n corresponds to the degree of cutting edge features, and a corresponds to the number of images for each degree of cutting edge feature. The database preferably contains at least 10,000 images.

[0019] Another advantage is that the cut edge is measured using optical measuring equipment, especially imaging methods and / or tactile measuring equipment.

[0020] A favorable improvement involves setting up the image display and user input in such a way that the evaluation of the cutting edge is performed based on a discrete scale. For example, the discrete scale could include evaluation points from 1 to 5, 1 to 10, or 1 to 100. Another favorable improvement involves setting up the image display and user input in such a way that the evaluation of the cutting edge is based on a comparison of multiple displayed cutting edges, particularly two or three displayed cutting edges. Therefore, multiple images are displayed simultaneously, where the user selects the better or worse cutting edge. These two evaluation methods can also be combined. The evaluation can be performed first based on a discrete scale and then based on a comparison.

[0021] Advantageously, the display of the image and user input include the following steps, which are performed in particular in the given order: - Cut edges that show differences in objective cut edge features, especially in single objective cut edge features; - If the evaluation is the same despite the differences in the objective cut edge features, the dataset is filtered so that only the following cut edges are presented to the user: cut edges that have a single degree of the objective cut edge features. - Repeat the previous steps.

[0022] For example, you could first show the user cut edge 1, and then show cut edge 2.

[0023] The table below shows the objectived cutting edge characteristics of cutting edge 1 and cutting edge 2, wherein the cutting edges have been measured, for example, in terms of burrs, roughness, and discoloration. The degree is then determined, which in this case is classified on a scale from 1 (very poor) to 5 (very good).

[0024] Cut edge 1: Cut edge 2: If a user rates cut edge 1 and cut edge 2 equally, for example, with a rating of 3, it can be inferred that burrs—despite being rated 1 (very poor) in cut edge 1 and 5 (very good) in cut edge 2—are meaningless to the user (Relevanz). If the ratings are only slightly off, for example, a rating of 2 for cut edge 1 and a rating of 3 for cut edge 2, it can be inferred that they are of low significance to the user. If there is a large off-target, it can be inferred that they are of high significance. Based on the rating differences, the cut edge feature—burrs—can be weighted in optimizing operating parameters.

[0025] Furthermore, for the first case (meaningless) and / or the second case (low significance), images with varying degrees of this cutting edge feature can be removed from the dataset. Since this cutting edge feature has no impact on the evaluation, the evaluation can be streamlined accordingly. Therefore, the dataset can be progressively simplified. Consequently, a personalized and / or optimal set of cutting edge features for the user can be easily and quickly obtained.

[0026] Preferably, a search algorithm for selecting the next image is used to obtain a robust quality fingerprint—that is, a dataset for determining subjective quality perception—using a small number of images to be displayed. The quality fingerprint can be validated for specific customers and / or customer groups and / or industries. Preferably, individualized operating parameters are then determined from this dataset, particularly based on materials and / or other boundary conditions.

[0027] Furthermore, it is advantageous to perform a comparison process, such as the Analytic Hierarchy Process (AHP), to evaluate the weights and / or the degree of cut edge features.

[0028] Another advantage is that the creation and / or optimization of the operating parameters of the laser cutting facility are based on the weighting of objective cutting edge features. Therefore, it is preferable to generate a set of operating parameters corresponding to the weighted cutting edge features. When user evaluations show significant differences across different degrees of a cutting edge feature, the objective cutting edge feature is assigned a larger weight; and when user evaluations show no difference, particularly no significant difference, across different degrees of a cutting edge feature, the objective cutting edge feature is assigned a smaller weight. In the case of a discrete scale such as 1, 2, ..., 9, 10, a significant difference can be, for example, two or three evaluation points, i.e., exceeding 20% ​​or 30% of the difference between the minimum and maximum evaluation points.

[0029] Preferably, the creation and / or optimization of operating parameters are performed offline. Therefore, subjective quality characteristics can be obtained independently of the specific process. It is conceivable that subjective quality characteristics are obtained before the first cutting process, and then operating parameters are created and / or optimized. Thus, optimal and / or individualized cutting parameters can be generated for the user from the very first cutting process. There is no need for the user to perform laser cutting for evaluation and optimization.

[0030] The object of the present invention is also achieved by a laser cutting apparatus having the features of claim 13. This laser cutting apparatus is used to laser cut a workpiece using individualized operating parameters, wherein the laser cutting apparatus includes a display device for displaying an image of the cut edge and for receiving user input, and wherein the laser cutting apparatus is configured according to the previously described method.

[0031] The object of the present invention is also achieved by a system comprising a laser cutting facility for laser cutting a workpiece and a display device, in particular a computer, laptop, smartphone, tablet or other wearable device, constructed independently of the laser cutting facility for displaying an image of the cutting edge and for receiving user input, wherein the system is configured according to the method described above, and wherein the system is further configured to display an image of the cutting edge on the display device and to receive user input by means of the display device.

[0032] Further details and advantageous improvements of the invention can be found in the following description, which further describes and illustrates exemplary embodiments of the invention. Attached Figure Description

[0033] In the attached diagram: Figure 1 A schematic diagram of the method according to the present invention is shown; Figure 2 A schematic diagram showing the display and evaluation of the cut edge is provided; Figure 3 A schematic diagram of the first cut edge is shown; Figure 4 A schematic diagram of the second cutting edge is shown; and Figure 5 A schematic diagram of the third cutting edge is shown. Detailed Implementation

[0034] Figure 1 Eight method steps for operating a laser cutting facility are schematically illustrated. First, according to step S10, multiple workpieces are processed during the laser cutting process to produce cutting edges with different cutting edge characteristics and degrees.

[0035] In step S12, the cutting edge is measured using an imaging measurement method, whereby roughness, burrs, and discoloration are quantitatively determined. Here, cutting edge features can be determined for each cutting edge. Furthermore, the cutting edge can be divided into regions to determine sub-features within these regions. The level of refinement in the measurement can be arbitrarily conceived.

[0036] In step S14, the image of the cut edge and its associated cut edge features are stored in the database. Therefore, for each cut edge or each cut edge region, there exists a data pair including the image of the cut edge and a set of acquired cut edge features. The database can then be provided to the user for evaluation.

[0037] In step S16, the image is displayed to the user on a display device on the laser cutting facility or on a computer, tablet, or smartphone. Figure 2 The image display, the display order, and user input are shown in detail.

[0038] In step S16, two or more cut edge images, which differ significantly in the degree of their cut edge features, are displayed to the user simultaneously or sequentially (particularly one after the other). The user then evaluates these images according to step S18. Next, in step S16A, it is checked whether sufficient information has been collected to evaluate the weight of the cut edge features. If this is the case according to B1, the evaluation ends. If this is not the case according to B2, then in step S16B, it is checked whether the user input causes the database to be adjusted according to condition B4. Database adjustment occurs when the user evaluates images of cut edges with significantly different degrees of cut edge features in the same or similar manner. The database can be simplified by displaying only images with one degree of the cut edge feature. If the user's evaluation indicates that the cut edge feature in question is meaningful, then according to condition B3, cut edges with different degrees of that cut edge feature are displayed. Another possibility is that users could use ratings to indicate at what point the cut edge becomes unusable. In this case, the meaning of the cut edge feature is only applicable up to a certain extent.

[0039] By having users rate the cut edges, the database is further narrowed, and the weights of each cut edge feature are closer to the user's subjective requirements. Once enough information is collected, multiple cut edge images with more complex sets of cut edge features can be displayed for further verification, where the user inputs their rating: which cut edge should be rated better. This is particularly useful when the degree varies across multiple cut edge features, or only slightly varies within a single cut edge feature. Finally, the cut edges and the user's expected rating can be shown to the user for verification purposes. If this meets the user's expectations, the evaluation can end. If not, the evaluation can be restarted or continued.

[0040] Following user input, step S20 determines the individualized cutting edge feature weights based on the user input. By associating the cutting edge features with the cutting edge images evaluated by the user, the meaning and significance of each cutting edge feature, i.e., its weight, can be inferred. The weights can preferably be determined by artificial intelligence.

[0041] Then, taking weights into account, individualized operating parameters are created and / or optimized according to step S22. Here, the cutting edge characteristics are related to one or more operating parameters. The operating parameters are created and / or optimized based on two criteria: cutting quality and cutting speed, where cutting quality is individualized for the application based on user input.

[0042] Finally, the workpiece can be laser-cut using individualized operating parameters in step S24.

[0043] Figures 3 to 5 Three different cut edges are shown. According to... Figure 3 The first cut edge 10 has noticeable burrs, which users might rate as "very poor". According to Figure 4 The second cutting edge 12 has unevenness that negatively impacts roughness. Users might rate it as "moderate." According to... Figure 5 The third cutting edge 14 has an optimal cutting edge, which is accompanied by a lower cutting speed.

Claims

1. A method for operating a laser cutting facility, the method comprising the following steps: a) Provide a dataset containing images of processed workpieces with cut edges and including objectified cut edge features associated with the images; b) Displaying an image of the cut edge from the dataset on a display device, wherein the cut edge varies according to the objectified cut edge features; c) User input to evaluate the displayed cut edges; d) Based on user input evaluating the cut edge, create and / or optimize user-individualized operating parameters for the laser cutting facility.

2. The method according to claim 1, further comprising the following step: e) Cut the workpiece using the created and / or optimized operating parameters.

3. The method according to claim 1 or 2, wherein, Providing a dataset includes the following steps: - Process the parts to produce a part with at least one cut edge; - Capture an image of the cut edge; - Measure the cutting edge to objectify the cutting edge features; - Assigning objective cut edge features to the image; and - The image and its associated objectified cut edge features are stored in the dataset.

4. The method according to claim 3, wherein, The processing of the component is carried out in such a way that a cutting edge is provided, the cutting edge having different combinations of objective cutting edge features.

5. The method according to claim 3 or 4, wherein, The measurement of the cut edge is performed using optical measurement equipment and / or tactile measurement equipment.

6. The method according to any one of the preceding claims, wherein, The display of the image and user input are performed in such a way that the evaluation of the cut edge is performed based on a discrete scale.

7. The method according to any one of the preceding claims, wherein, The display of the image and user input are performed in such a way that the evaluation of the cutting edge is performed based on a comparison of multiple displayed cutting edges.

8. The method according to any one of the preceding claims, wherein, The display of the image and user input are performed in such a way that the evaluation of the cut edge is first performed based on a discrete scale and then the evaluation of the cut edge is performed based on a comparison between a plurality of displayed cut edges.

9. The method according to any one of the preceding claims, wherein, The display of images and user input include the following steps: - Shows differences in cut edges in terms of objective cut edge features; - If the evaluation is the same despite the differences in the objectived cut edge features, then filter the dataset so that only cut edges with a single degree of the objectived cut edge features are presented to the user. - Repeat the previous steps.

10. The method according to any one of the preceding claims, wherein, The creation and / or optimization of the operating parameters of the laser cutting facility are based on the weights of the objective cutting edge features. Specifically, when user evaluations differ under varying degrees of an objective cutting edge feature, this objective cutting edge feature is given greater weight. Specifically, when user evaluations are not different under different degrees of a cutting edge feature, the objective cutting edge feature is assigned a smaller weight.

11. The method according to any one of the preceding claims, wherein, The creation and / or optimization of the operating parameters are performed offline.

12. The method according to any one of the preceding claims, wherein, The image of the cutting edge is generated such that the cutting edge extends in the image plane of the image.

13. A laser cutting apparatus for laser cutting workpieces using individualized operating parameters, wherein, The laser cutting facility includes a display device for displaying an image of the cutting edge and a display device for receiving user input, wherein the laser cutting facility is configured according to the method according to any one of the preceding claims.

14. A system comprising a laser cutting apparatus and a display device, the laser cutting apparatus being used to laser cut a workpiece, the display device being constructed independently of the laser cutting apparatus, the display device being used to display an image of the cut edge and to receive user input, wherein... The system is configured according to the method of any one of claims 1 to 12, and wherein the system is further configured to display an image with a cut edge on the display device and to receive user input by means of the display device.

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